diff --git a/modules/memstats.py b/modules/memstats.py
index d43e5bbfa..cb43f246c 100644
--- a/modules/memstats.py
+++ b/modules/memstats.py
@@ -1,3 +1,5 @@
+import re
+import sys
 import os
 import psutil
 import torch
@@ -56,3 +58,48 @@ def ram_stats():
         return ram
     except Exception:
         return { 'used': 0, 'total': 0 }
+
+
+class Object:
+    pattern = r"'(.*?)'"
+
+    def __init__(self, name, obj):
+        self.id = id(obj)
+        self.name = name
+        self.fn = sys._getframe(2).f_code.co_name
+        self.size = sys.getsizeof(obj)
+        self.refcount = sys.getrefcount(obj)
+        if torch.is_tensor(obj):
+            self.type = obj.dtype
+            self.size = obj.element_size() * obj.nelement()
+        else:
+            self.type = re.findall(self.pattern, str(type(obj)))[0]
+            self.size = sys.getsizeof(obj)
+    def __str__(self):
+        return f'{self.fn}.{self.name} type={self.type} size={self.size} ref={self.refcount}'
+
+
+def get_objects(gcl={}, threshold:int=0):
+    objects = []
+    seen = []
+
+    for name, obj in gcl.items():
+        if id(obj) in seen:
+            continue
+        seen.append(id(obj))
+        if name == '__name__':
+            name = obj
+        elif name.startswith('__'):
+            continue
+        try:
+            o = Object(name, obj)
+            if o.size >= threshold:
+                objects.append(o)
+        except Exception:
+            pass
+
+    objects = sorted(objects, key=lambda x: x.size, reverse=True)
+    for obj in objects:
+        shared.log.trace(obj)
+
+    return objects
diff --git a/modules/sd_models.py b/modules/sd_models.py
index df49b4918..2de127347 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -1050,27 +1050,27 @@ def unload_model_weights(op='model'):
         shared.compiled_model_state.compiled_cache.clear()
         shared.compiled_model_state.req_cache.clear()
         shared.compiled_model_state.partitioned_modules.clear()
-    if op == 'model' or op == 'dict':
-        if model_data.sd_model:
-            if not shared.native:
-                from modules import sd_hijack
-                move_model(model_data.sd_model, devices.cpu)
-                sd_hijack.model_hijack.undo_hijack(model_data.sd_model)
-            elif not ('Model' in shared.opts.cuda_compile and shared.opts.cuda_compile_backend == "openvino_fx"):
-                disable_offload(model_data.sd_model)
-                move_model(model_data.sd_model, 'meta')
-            model_data.sd_model = None
-            devices.torch_gc(force=True)
-            shared.log.debug(f'Unload weights {op}: {memory_stats()}')
-    elif op == 'refiner':
-        if model_data.sd_refiner:
-            if not shared.native:
-                from modules import sd_hijack
-                move_model(model_data.sd_refiner, devices.cpu)
-                sd_hijack.model_hijack.undo_hijack(model_data.sd_refiner)
-            else:
-                disable_offload(model_data.sd_refiner)
-                move_model(model_data.sd_refiner, 'meta')
-            model_data.sd_refiner = None
-            devices.torch_gc(force=True)
-            shared.log.debug(f'Unload weights {op}: {memory_stats()}')
+    if (op == 'model' or op == 'dict') and model_data.sd_model:
+        shared.log.debug(f'Current {op}: {memory_stats()}')
+        if not shared.native:
+            from modules import sd_hijack
+            move_model(model_data.sd_model, devices.cpu)
+            sd_hijack.model_hijack.undo_hijack(model_data.sd_model)
+        elif not ('Model' in shared.opts.cuda_compile and shared.opts.cuda_compile_backend == "openvino_fx"):
+            disable_offload(model_data.sd_model)
+            move_model(model_data.sd_model, 'meta')
+        model_data.sd_model = None
+        devices.torch_gc(force=True)
+        shared.log.debug(f'Unload {op}: {memory_stats()} after')
+    elif (op == 'refiner') and model_data.sd_refiner:
+        shared.log.debug(f'Current {op}: {memory_stats()}')
+        if not shared.native:
+            from modules import sd_hijack
+            move_model(model_data.sd_refiner, devices.cpu)
+            sd_hijack.model_hijack.undo_hijack(model_data.sd_refiner)
+        else:
+            disable_offload(model_data.sd_refiner)
+            move_model(model_data.sd_refiner, 'meta')
+        model_data.sd_refiner = None
+        devices.torch_gc(force=True)
+        shared.log.debug(f'Unload {op}: {memory_stats()}')